Federico is correct, as long as your continous variable
is 0 (and not missing) when the binary variable is 0. If
it the continous variable is missing when the binary
variable is 0, you can create a new depvar that has the
correct properties:

gen newdepvar=cond(var1==0,0,var2)
and use this as the depvar.
hth,
Jeph
On 5/6/2013 10:40 AM, Federico Belotti wrote:

Dear Beatrice,

if my understanding of your problem is correct, you can
solve your issue by directly specifying as depvar your
continuous variable. -tpm- will automatically generate
(for the first part regression) a dummy equal to 1 when
the
continuous variable is greater than 0. My suggestion is
to normalize your continuous variable in order to get a

depvar that is bounded between 0 and 1.
HTH, Federico
On May 6, 2013, at 4:08 PM, Beatrice Muriithi wrote:

Thank you Jeph, I have installed tpm and tried to
execute the model. Unfortunately tpm requires that the
dependent
variables for both parts are the same (error:"The
dependent variable must be the same in both equations"
r(110)).
In my case, the dependent variable are different, the
first stage has a discrete variable (0,1) and the second
part
has continuous variable but include 0 and 100
(proportion). I will appreciate any further insights.
Regards

I have case of sample selection for which i would wish
to use double hurdle model. The dependent variable for
the first stage is a discrete variable therefore i can
use Probit model. The dependent variable for the second
stage is fractional response variable (contains 0-100 -
percent). Is it ok if i use GLM (applied mainly for
fractional response variable problem) in the second
stage? and if yes, is there a do program that can assist
me
in this procedure to get the correct standard errors
accounting for the first stage estimation?